Today, mobile communication systems have a serious problem that a resource of frequencies is increasingly becoming insufficient with increasing popularity of broadband communication. Techniques such as a cognitive radio communication technique have been proposed to solve the above problem. In the cognitive radio communication technique, a communication terminal apparatus or the like checks conditions in circumstances in terms of radio waves, and changes a frequency or a communication method depending on the conditions.
A method of realizing the cognitive radio communication is, for example, to detect a frequency which is not used at a point of time when communication is tried to be started, and communication is performed using the detected frequency. To realize this method, a signal detector is used to detect a frequency which is being used or a frequency which is not being used.
A conventional technique for detecting a signal using a signal detector is to determine whether there is a signal or not based on a ratio of a maximum eigenvalue to a minimum eigenvalue of an autocorrelation matrix of a received signal. More specifically, in this conventional technique, the ratio of the maximum eigenvalue to the minimum eigenvalue is compared with a threshold value. If the ratio is equal to or greater than the threshold value, it is determined that there is a signal, but otherwise it is determined that there is no signal.
In another conventional technique, to inhibit eigenvalues from being disturbed by noise, eigenvalues are determined while cyclically shifting column vectors of a signal matrix thereby estimating a direction in which a radio wave is coming. In another conventional technique, a minimum eigenvalue is detected from eigenvalues of a correlation matrix of signals received by a plurality of antennas. The detected minimum eigenvalue is regarded as noise, and noise is removed by subtracting the minimum eigenvalue from the maximum eigenvalue and a second eigenvalue thereby obtaining eigenvalues including no noise components. Using the resultant eigenvalues including no noise components, a direction in which a radio wave comes and a space angle are estimated. In another technique, when SNR is estimated using a disturbance correlation matrix, minimum eigenvalues are regarded as noise, and an average of minimum eigenvalues is calculated to improve noise estimation accuracy.
Descriptions of related techniques may be found, for example, in Japanese Laid-open Patent Publication No. 2007-309846, Japanese Laid-open Patent Publication No. 2007-274250, Japanese Laid-open Patent Publication No. 2007-220236, Japanese Laid-open Patent Publication No. 2008-85894, Japanese Laid-open Patent Publication No. 2008-546349, etc.
Descriptions of related techniques may also be found, for example, in Y. Zeng and Y. Liang, “Eigenvalue-Based Spectrum Sensing Algorithms for Cognitive Radio,” IEEE Trans. on Commun., Vol. 57, No. 6, June 2009, etc.